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testing and certification_OLAP_data_mining

hi guyzs I have a quizz and would like your views. feel free to answer;

1. Which best describes data discovery when designing a data warehouse?
a. The process of investigating source system data to understand its characteristics and impact on the warehouse design.
b. The process of investigating end user requirements to understand their characteristics and impact on the warehouse design.
c. The process of identifying performance trends.
d. The process to check current performance status.
e. The process of comparing metric performance across time periods.
f. The process to find anomalies or identify best/worst performing items and to identify items that do not meet defined criteria.
g. The process to find correlations in the data or to perform iterative analysis.

2. Which best describes data mining?
a. The process of investigating source system data to understand its characteristics and impact on the warehouse design.
b. The process of investigating end user requirements to understand their characteristics and impact on the warehouse design.
c. The process of identifying performance trends.
d. The process to check current performance status.
e. The process of comparing metric performance across time periods.
f. The process to find anomalies or identify best/worst performing items and to identify items that do not meet defined criteria.
g. The process to find correlations in the data or to perform iterative analysis.

3. When optimizing the query response time of the data warehouse which of the following does not apply?
a. Account for all possible queries.
b. Prioritize queries based on importance and frequency of use.
c. Design to meet the bulk of the queries (the 80-20 rule).
d. Determine the amount and level of granularity of the data.

5. Which of the following does not justify building a data warehouse iteratively?
a. Allows for change, corrections or enhancements.
b. User requirements may change or become better defined as data is made available.
c. User work flow may change.

6. Which of the following is the most efficient routine to execute for updating fact data (maintenance job)?
a. Ignore the changes
b. Wait until the data is cleaned
c. Drop data that was loaded and reload the data
d. Capture and apply changes by comparing files to develop a delta file and then applying the delta file by using insert based on delta records
7. If a change occurs in the attribute relationships in the data warehouse, foreign keys
in lookup tables may have to be changed, compound primary keys in the fact and
lookup tables may have to be changed, or the aggregate table values may change.
Which of the following is the least expensive maintenance job in this case?
a. Update foreign keys in lookup tables
b. Update primary keys in lookup and fact tables
c. Re-aggregate the aggregate tables.

8. Lookup tables are refreshed to add new data from the source systems. Which method is the most difficult?
a. Extract is run once to populate the data warehouse.
b. Existing table is dropped, extract is re-run to capture current information, and the table is loaded with new extract.
c. Deltas are captured as they occur in the source system and changes are applied on continual basis.
d. Extract is re-run to capture current information, new extract and old lookup file is compared, new delta file is generated, and delta file is loaded.

9. Which of the following is most descriptive of users’ reporting cycles?
a. Ad-hoc analysis is done regularly the average user.
b. Reports that are run daily will be the same as reports run weekly.
c. Users perform analysis according to the availability of data

10. Which of the following best describes the goal of developing query profiles?
a. Goal is to understand the characteristics of the data.
b. Goal is to define user needs.

11. Which of the following applies when doing comparison reports?
a. Length of the period of comparison and level of detail remain the same.
b. Number of years that provide meaningful comparison will vary.
c. Older data is still meaningful if the business changes and new products and
services replace older ones.

12. Which of the following functions is typically supported by a data quality profiling tool?
a. Suggesting standard formats for data within a column.
b. Allowing the specification of synonym tables for standardization.
c. Determining the maximum, minimum, and average field size of a column.

13. Which of the following functions is typically supported by a data cleansing tool?
a. Transforming free-form text into discrete fields based on patterns, data types,
and business-specific rules.
b. Determining whether the values in a column are unique.
c. Performing pattern recognition for data in a column.

14. Partitioning divides a logical table into several small tables based on a definable data group. Time is the most common benefit dimension by which data warehouses are partitioned. Which of the following is a benefit of time-based partitioning?
a. Allows for a distributed data warehouse.
b. Provides greater flexibility in batch processing.
c. Greatly reduces the backup process